
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "158"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 93 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 89 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.254754	-0.756504	0.225174	-0.087177	0.319267	5.564934	0.152581	0.223171	0.7633	0.7880	0.2567	16.777262	23.612308
2459593	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.183471	-0.774456	0.041682	-1.083884	0.128241	-0.193486	-0.006226	1.432058	0.7292	0.7321	0.2546	6.550709	6.421145
2459592	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	0.238805	-0.469452	-0.463482	-0.096389	1.870697	0.629264	1.654313	0.395830	0.0307	0.0336	0.0023	nan	nan
2459591	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.647272	-0.765526	-0.174324	-1.019802	-0.060343	-0.530150	0.912431	5.169886	0.6577	0.6850	0.3756	6.384584	6.523215
2459590	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.600042	-0.659296	0.086523	-0.992819	1.841368	3.051854	1.482089	4.688938	0.6613	0.6818	0.3677	5.271896	5.610384
2459589	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.003261	-0.981641	0.382187	0.400094	0.746183	0.573848	-0.367499	0.031023	0.6909	0.7003	0.2969	10.565826	11.124381
2459588	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.001871	-1.131521	-0.053798	-1.220006	0.533629	-0.155226	-0.030216	0.748269	0.7718	0.7662	0.2197	10.012506	8.995300
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	1.829770	-0.207677	0.308498	-0.927833	0.823874	0.268786	0.675349	5.303962	nan	nan	nan	0.000000	0.000000
2459586	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	306.757337	312.837004	inf	inf	10.063494	15.413812	164.245123	666.440841	nan	nan	nan	0.000000	0.000000
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	8.546271	2.822807	4.319584	3.743051	5.442229	3.608239	3.559168	10.295606	0.0329	0.0349	0.0012	0.000000	0.000000
2459584	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.198344	-0.475026	0.897521	2.626369	1.798491	0.475242	0.713321	2.516412	0.6019	0.6245	0.3662	5.515734	7.138461
2459583	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.771487	0.226329	1.171020	1.494987	3.450620	1.950740	2.300248	6.412776	0.6578	0.6824	0.3892	4.763773	4.246214
2459582	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.704947	-0.026112	0.605178	1.372665	3.313966	2.007102	0.652271	8.053067	0.6600	0.6826	0.3910	5.348446	5.171305
2459581	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.288619	-0.078515	0.861672	0.925958	2.687079	1.963762	1.997294	9.032394	0.6650	0.6860	0.3864	6.609391	5.779470
2459580	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.625086	-0.179921	0.329629	1.130315	3.044407	2.030827	2.593846	6.531729	0.6610	0.6835	0.3858	5.153817	4.220099
2459579	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459578	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	-0.782341	-0.156934	-0.566084	-0.418804	1.438499	0.792566	-0.789615	9.860863	0.0306	0.0322	0.0017	nan	nan
2459577	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.841326	-0.042768	0.680069	0.880298	2.703629	2.777284	2.925258	9.088889	0.6595	0.6828	0.3827	5.298965	5.773882
2459576	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.212334	-0.148820	0.376537	0.574312	2.683631	3.373385	5.141816	7.474445	0.6831	0.7056	0.3846	6.597629	6.875130
2459575	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.568127	1.256982	0.594585	0.745632	2.819542	4.510832	0.857353	1.274128	0.7444	0.7522	0.3334	18.028827	16.219903
2459574	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.885206	3.581901	0.513630	0.730583	0.828888	2.346386	0.386637	2.621323	0.6815	0.6947	0.3769	6.466103	6.392901
2459573	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.634854	0.324760	1.426256	1.887104	4.431841	2.290870	2.299199	9.510105	0.6746	0.7023	0.3876	5.846733	5.044556
2459572	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.162845	-0.268532	0.397383	0.772842	1.820355	3.222961	1.057250	14.208380	0.6850	0.7081	0.3821	7.122530	5.846557
2459571	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	-0.475374	-0.088821	-0.821353	-0.599338	2.100404	8.931344	-0.791193	4.649417	0.0306	0.0316	0.0018	nan	nan
2459570	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459569	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.314544	-0.966674	0.580017	0.696170	0.966153	1.526363	0.613813	0.809920	0.7491	0.7623	0.2458	6.708851	5.720806
2459566	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.712085	0.044430	0.962118	1.269383	2.547354	0.994962	0.633569	7.387687	0.6683	0.6910	0.4032	3.697621	3.267761
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	1.033212	1.033212	1.033557	1.033557	0.000000	0.000000	0.000000	0.000000	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.083145	-0.609450	0.662188	-0.359910	0.949238	2.498351	1.938837	7.609439	0.6850	0.6994	0.3986	4.396969	4.397838
2459563	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.181217	0.561901	2.292051	15.880347	3.201101	2.575473	2.840513	13.976499	0.6846	0.6959	0.3907	4.212152	4.150024
2459562	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.495662	-1.446264	-2.405453	-1.320866	-1.428818	-2.804063	-0.077688	2.129285	0.6785	0.6961	0.3949	3.912456	3.467731
2459561	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.826674	2.813429	1.955761	1.888129	0.400438	0.432664	-2.085003	-0.599561	0.6614	0.6833	0.3832	3.097991	2.835284
2459560	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.542283	-1.039961	-0.893305	-0.851606	-1.509978	-1.804942	-0.580075	3.867181	0.6734	0.6963	0.3981	4.228271	3.484239
2459559	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.455526	0.494450	0.414425	0.691576	2.252410	1.281780	1.305976	3.367702	0.6781	0.6994	0.3910	3.382931	3.044437
2459558	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0294	0.0298	0.0011	nan	nan
2459556	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.485835	0.250257	0.796438	1.984372	3.177139	1.786088	3.567709	20.433351	0.6774	0.6952	0.3925	4.181482	3.896623
2459554	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.6875	0.7053	0.3991	nan	nan
2459553	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.6725	0.6916	0.3962	nan	nan
2459552	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.951054	0.102617	0.879888	0.352211	2.471892	1.204165	0.075371	17.742230	0.6926	0.7085	0.3931	9.847410	9.610249
2459551	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.320382	0.098285	0.513324	0.773132	2.594013	1.685298	0.675440	7.474464	0.6846	0.7032	0.3905	3.598527	3.352203
2459550	RF_maintenance	-	99.18%	99.18%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0318	0.0318	0.0005	nan	nan
2459549	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.674325	-0.228066	0.856787	1.276387	3.596992	1.450466	1.039867	12.532894	0.6724	0.6915	0.4114	3.530473	3.420398
2459542	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.245542	-0.062241	0.017863	0.060286	1.314489	1.607580	0.567552	9.042930	0.7341	0.7391	0.3657	3.224722	3.099617
2459541	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459540	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.523926	0.759003	0.738722	0.941531	3.436034	0.613810	1.830052	6.083219	0.7374	0.7428	0.3499	3.698074	3.197516
2459536	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459535	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.543334	0.570013	0.812849	0.861395	2.842592	0.052344	3.428285	6.735670	0.7755	0.7681	0.3634	4.206806	3.432055
2459534	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.325822	0.763710	1.100742	0.909329	3.334044	0.242041	2.231543	5.815729	0.7685	0.7597	0.3533	6.689626	6.002135
2459533	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.037574	0.590600	1.152325	1.424725	4.059680	1.428571	0.931540	17.642982	0.7047	0.7196	0.4016	4.296133	3.561143
2459532	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	2.615096	0.726418	1.635537	2.474128	4.026046	1.704340	1.227210	10.967288	0.7085	0.7228	0.4013	3.846613	3.621670
2459530	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459522	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459513	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	-0.418784	-0.180218	-0.549907	-0.053323	-0.281129	1.312640	-0.768989	6.503707	0.0305	0.0315	0.0010	nan	nan
2459508	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.360502	-0.205721	1.955777	1.859575	2.600743	1.716672	3.374664	3.972346	0.9085	0.9392	0.1883	0.000000	0.000000
2459505	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.921389	-0.473966	-0.222519	1.462192	1.876025	1.527977	5.143553	3.743903	0.0944	0.0800	0.0050	1.161795	1.143894
2459503	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.678387	0.028906	1.040801	2.029129	0.708651	1.074764	3.652294	1.897809	0.8769	0.8691	0.4275	0.000000	0.000000
2459501	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	1.226371	0.777977	1.407079	1.560830	3.337277	0.302191	1.158659	0.618029	0.0966	0.0803	0.0096	0.000000	0.000000
2459500	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	2.419750	1.386960	2.551933	1.791232	1.758097	1.886049	2.179072	1.172087	0.0744	0.0779	0.0075	0.000000	0.000000
2459499	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	3.019858	2.148652	3.104093	2.577876	1.946942	2.362945	6.220302	4.077264	0.0844	0.0723	0.0057	0.000000	0.000000
2459498	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	2.638456	1.591875	1.591684	1.896566	1.250938	2.036690	0.830849	1.625810	0.0822	0.0745	0.0075	0.000000	0.000000
2459497	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	2.177997	1.442962	1.136606	1.691700	0.148042	2.008896	3.283337	1.628091	0.0946	0.0778	0.0110	0.000000	0.000000
2459496	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	1.074483	1.530274	0.700670	1.675402	-0.310092	2.284613	6.972988	3.381967	0.0474	0.0847	0.0046	0.000000	0.000000
2459495	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	2.652548	1.104463	1.590856	1.429953	0.980264	2.007193	0.190384	1.398749	0.0891	0.0983	0.0103	0.000000	0.000000
2459494	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	3.152384	2.487086	2.696815	2.289746	1.195492	2.592290	3.347715	4.627167	0.0905	0.0793	0.0113	0.000000	0.000000
2459492	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.841036	-1.557583	-1.282274	-0.728928	2.694450	4.304734	6.826988	23.150732	0.1058	0.0673	0.0069	0.000000	0.000000
2459491	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	1.292368	0.067044	0.370763	0.094482	8.133648	0.180104	15.800916	4.068735	0.0968	0.0818	0.0068	0.000000	0.000000
2459490	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.443941	-0.668111	-1.358653	-1.192587	2.274619	0.023611	8.661424	15.651585	0.7422	0.8051	0.3670	0.000000	0.000000
2459489	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.094622	0.171402	-1.579283	-0.607549	4.629694	2.269148	7.298215	9.465013	0.7587	0.8107	0.3191	0.000000	0.000000
2459488	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.317477	-0.022310	-0.419102	0.232637	2.619329	1.486700	19.873270	19.036348	0.7595	0.8124	0.3445	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 158 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 158, Node 12:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 158: 2459617

Antenna 158: 2459616

Antenna 158: 2459615

Antenna 158: 2459614

Antenna 158: 2459613

Antenna 158: 2459612

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Antenna 158: 2459609

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Antenna 158: 2459588

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Antenna 158: 2459527

Antenna 158: 2459524

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Antenna 158: 2459513

Antenna 158: 2459508

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶